Preprints
https://doi.org/10.5194/egusphere-2024-2414
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2024-2414
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
20 Aug 2024
| 20 Aug 2024
Air Pollution in The Upper Troposphere: Insights from In-Situ Airplane Measurements (1991–2018)
Abstract. Long-lived atmospheric species like carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and CFCs exhibit discernible trends reflecting anthropogenic emissions, with increases observed in CO2, CH4, N2O, and decreases in CFCs. Conversely, trends for short-lived species like carbon monoxide (CO) and nitrogen oxides (NOx) remain less understood due to rapid chemistry and limited upper tropospheric observations. We utilize extensive in-situ CO measurements spanning 2012–2023, supplemented by prior airplane campaigns from 1991–2019, to examine short-term fluctuations in CO influenced by anthropogenic emissions and rapid chemical removal. Comparisons with MOPITT satellite data and chemistry budgets from 1948–2003 simulations further elucidate the interplay of sources and sinks, revealing the significant impact of chemistry on CO profiles and trends.
How to cite. Wang, K.-Y., Nedelec, P., Thouret, V., Clark, H., Wahner, A., and Petzold, A.: Air Pollution in The Upper Troposphere: Insights from In-Situ Airplane Measurements (1991–2018), EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2414, 2024.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics: Andreas Petzold
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.Download & links
Download & links
- Preprint
(16968 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2024-2414', Anonymous Referee #1, 24 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Kuo-Ying Wang, 28 Feb 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC1-supplement.pdf
-
AC4: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC4-supplement.pdf
-
AC1: 'Reply on RC1', Kuo-Ying Wang, 28 Feb 2025
-
RC2: 'Comment on egusphere-2024-2414', Anonymous Referee #2, 05 Oct 2024
Review of “Air Pollution in The Upper Troposphere: Insights from
In-Situ Airplane Measurements (1991-2018)” by Kuo-Ying Wang, Philippe Nedelec, Valerie Thouret, Hannah Clark, Andreas Wahner, and
Andreas Petzold
General Comments:
- This paper tries to do too much with disparate data sets.
- Some of the datasets are not referenced adequately.
- The authors do not explain why it is legitimate to compare a few older campaigns and more recent and denser datasets.
- It is not clear that some of the analysis and results, especially for the trends, are robust.
- The model simulations do not go beyond 2003 and used fixed anthropogenic emissions. There is very little overlap with MOPITT and IAGOS so there is limited value in the comparisons.
- MOPITT CO retrievals are not point measurements like for the IAGOS aircraft and Mauna Loa observatory. How can you compare MOPITT partial column retrievals with point measurements ? What have other studies done?
- The authors do not discuss their analysis and findings in the context of previous publications that have looked at CO emissions and atmospheric CO trends in and downwind of Asia and in the Northern hemisphere.
- The paper is very long, it has 14 figures. There are typos in several places. A careful re-reading is suggested.
- There is another paper referred to as [Wang et al., 2024] submitted to another journal by the same group of authors with overlapping content (PDF is available online). That paper used the HYSPLIT lagrangian model. HYSPLIT is not used in this paper under review by EGUsphere yet it is in the manuscript I am reviewing in the acknowledgements. How are the 2 papers complementary?
- In short, the paper is hard to read, has very limited comparison of its “findings” with other studies and it is not clear what results are reliable and new in this paper.
Other paper by the same authors with significant overlap:
Wang, K.-Y., P. Nédélec, V. Valerie, H. Clark, A. Wahner, et al., In-Situ Monitoring and Origins of Increased Air Pollutants in the North Pacific Upper Troposphere: Insights from PGGM/IAGOS Carbon Monoxide Measurements aboard the China 540 Airlines A340-300 Commercial Aircraft (July 2012 - February 2013), Scientific Rep., Submitted, 2024.
https://www.researchsquare.com/article/rs-3938611/v1
Detailed comments
Page 1
- The work mostly deals with carbon monoxide, should the title make that more clear
- Fix Authors’ affiliations numbering to only show Laboratoire d’Aérologie once in the list and refer to it with the same number for the authors from that lab. Same thing for Forschungszentrum Jülich
Abstract:
- First general sentence on long-lived gases does not belong in the abstract. Focus on summarizing your work on CO.
- Lines 4-6. Be more specific:
- what in situ data composite are you using for your analysis: dataset name, main characteristics, temporal coverage
- Region you are focusing on
- What does “short-term fluctuations” mean in the context of your multi-year analysis?
- Lines 6-9.
- Which MOPITT data product are you using and over what time period?
- Why use model results spanning 1948-2003, a period which does not overlap with the “extensive insitu CO measurements spanning 2012-2023”?
- Introduction:
- Lines 18-20:
- What “complex interactions” are you referring to in this sentence?
- “... interactions with various Earth system components such as the lithosphere, biosphere, hydrosphere, and cryosphere, particularly within the troposphere”, is this long list relevant here for your work on CO?
- Lines 23-26:
- Missing references:
- mention UV-B in the production of OH radicals and give reference
- is the CO+OH reaction temperature dependent? give reference
- Line 28: remove “emissions”. Satellite technique do not observe emissions directly.
- Lines 36: what do PGGM and IAGOS stand for?
- Line 50-54: this paragraph is background literature information and it belongs before you go over what your study and paper are about.
- Lines 50-51: be more specific re. which region this statement is for.
- Lines 52-55: Add Clark et al., 2015 in the references listed here.
- Lines 40-43. You present results here. Are they published in a peer reviewed paper already?
- The GTE campaigns only lasted a month or two and therefore these datasets are snapshots in time and space and cannot be used to derive annual means like you do here. PEM-West A : Sept-Oct 1991. PEM-West B: March 1993. Overview of flow conditions during these 2 campaigns: https://www-gte.larc.nasa.gov/pem/pemb_map.htm and https://www-gte.larc.nasa.gov/pem/pemb_rslt.htm
- Give the reference for the CO emission estimates for Asia (which countries?) and North America (Canada + US?) and provide information about what source categories are included.
- Explain if/why it makes sense to compare 1990s campaign means to more recent means from denser observations.
- Lines 46-49: what is the reference for this and how is it relevant here?
- Lines 55-59: It is not clear that the paper results are new insights. There have been a lot of publications on IAGOS and other CO data sets including some specifically on upper tropospheric CO over the Pacific Ocean [Smoydzin and Hoor, 2022].
Smoydzin, L. and Hoor, P.: Contribution of Asian emissions to upper tropospheric CO over the remote Pacific, Atmos. Chem. Phys., 22, 7193–7206, https://doi.org/10.5194/acp-22-7193-2022, 2022.
- Data and Methods
- Section 2.1.2:
- Lines 76-80: Why bring up CO2 measurements at Mauna Loa in this section on aircraft measurements? It seems out of place.
- Can you please explain why you focus on the upper troposphere in the sentence Lines 81-83?
- Line 83-85: Give a reference for the emissions growth during 1970-1994.
- Figure 1: several typos in the caption for plots a) and f). What is “Russia and Asia-Stan” in plot f).
- Lines 86-89: Specify which specific months the GTE PEM-WEST A, PEM-WEST B and TRACE-P took place. Give a few more references on publications from these campaigns, for ex [Bey et al., 2001].
- Lines 90-91: Check the sentence: “which marked the end of steady CO emission growth and significant growth thereafter, particularly from China”. The temporal patterns describe could be more clear and specific.
- Line 91: [Streets et al., 2006] presents an updated inventory of anthropogenic CO emissions in China. You need other references here to support your description of the interannual changes in emissions
- Line 94: HIPPO was not a NASA funded campaign.
- Section 2.1.3:
- Lines 105-106: ESRL does not exist anymore so use NOAA Global Monitoring Laboratory. Provide Latitude, Longitude and Altitude for the in situ measurements. Where did you get the Mauna Loa in situ CO measurements? The reference of Andrews et al. 2009 does not cover the Mauna Loa in situ CO measurements and the ftp location provided is obsolete. What instruments were used for the measurements, what time period are you looking at and mention what calibration scale the measurements are on.
- Lines 107-109: MLO CO measurements are not unique. There are other sites with CO in situ or discrete sample measurements. Replace verifying with evaluating, observed with derive and satellite measurements with satellite retrievals. Why mention the IMS model here ? It has not been introduced yet.
- Section 2.2:
- This sentence is too vague “The openly available MOPITT data are extensively utilized in documenting CO variations associated with various atmospheric processes.”
- Which version of the MOPITT retrievals are you using? What altitudes are the CO retrievals sensitive to?
- Section 2.3:
- Replace technological with anthropogenic in title
- Which EDGAR inventory version are you using? Provide necessary description: spatial and temporal resolution, source categories etc…
- Provide a more recent reference for that inventory and justify why this is a good and useful inventory for 1970-2020.
- Line 123: China appears twice
- How do you know that the EDGAR inventory for 1970-2020 is accurate and captures the real trends in emissions?
- Section 2.4:
- What is the spatial resolution of the CTM IMS? Do you use reanalyses for the transport? What is included in the chemistry part of the model?
- What species have you validated the model for? Does the model conserve mass?
- What meteorological fields are used?
- There is very little temporal overlap between the model simulations and the IAGOS observations or MOPITT retrievals. Why end the simulations in 2003? What is the goal of using model simulations with constant anthropogenic emissions when there were known trends in regional emissions over the long time periods simulated? The value of the modeling in this study is not made clear.
Bey, I., D. J. Jacob, J. A. Logan, and R. M. Yantosca, Asian chemical outflow to the Pacific: Origins, pathways and budgets, J. Geophys. Res., 106, 23,097–23,114, 2001.
- Results
Comments section 3.1:
- The authors refer to a composite of campaigns results as “time series long-term” measurements. A time series is typically for one type of measurement at one location. Please revise what you call these.
- What are you plotting in Figure 2:
- Are min, max, 25th, 50th and 75th percentiles for monthly mean data for the different available datasets for a lat/lon region and altitude range?
- Did you deseasonalize the CO data for section 3.1?
- Why does it make sense to look at trends from this composite of very different datasets and with very few data points in the early years (and later years for Fig 3) ?
- How did you compute the trends and are they significant given the very uneven temporal data coverage?
- Several figures are missing a legend or text in the caption for the colors and symbols used, for example Figure 2. Please explain the different colors, different symbols and the vertical bars.
- Some description in the text or in the figures is redundant, maybe you can reduce the redundancy to reduce the text and clutter on figures, for example see Figure 2.
Wang, H., Lu, X., Jacob, D. J., Cooper, O. R., Chang, K.-L., Li, K., Gao, M., Liu, Y., Sheng, B., Wu, K., Wu, T., Zhang, J., Sauvage, B., Nédélec, P., Blot, R., and Fan, S.: Global tropospheric ozone trends, attributions, and radiative impacts in 1995–2017: an integrated analysis using aircraft (IAGOS) observations, ozonesonde, and multi-decadal chemical model simulations, Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, 2022.
Comments section 3.2:
- Clarify which datasets you are using here and what altitude ranges you used for UT and LT.
- You compute trends on data that have strong seasonality and irregular temporal (and likely spatial) coverage. Explain why your approach works and if it is robust?
- Figure 4 is “cluttered” and hard to read. Equations above left and right plots are missing “+” sign.
- Put labels for subplots in a figure so the reader follows what plot you refer to when you make a statement in the text.
- Plot ”a.” top left for CO shows the equation for UT CO is 83.9 + 0.0x so no trend while the plot below shows 83.9+0.02x and in Line 183 you write “CO trends (why plural?) in UT show positive values” So if you compute a slope of 0.02 ppb/yr, it is basically no detectable trend.
- Are there end effects on your trend calculations?
- Compare with other studies
- So you compute negative trends for UT H2O? Can you compare with other published studies?
Comments section 3.3:
- Clarify which datasets you are using here and how you derived annual profiles
- Is it reliable to compute trends over a short period: 2012 to 2018? What else could have impacted the interannual variability of CO over this short time period besides changes in the magnitude of anthropogenic emissions in Asia?
Comments on section 3.4:
- Why do you end the model simulation in 2003 and does it make sense to extrapolate the model linearly after 2003?
- Isn’t there too little overlap between the model simulation and the MOPITT retrievals and IAGOS measurements?
- What initial conditions did you use for your model simulation? The modeled UT CO seems very low (<60 ppb) early on.
- What emissions did you use in the model for the different sources categories that matter for CO ? Do the emissions have a seasonal cycle? Only EDGAR and an older reference for it is mentioned in section 2.4
- Did I understand correctly that you use the same emissions for all years?
- Lines 139:140 in section 2.4
- Why can you use these simulations to evaluate “what controls long-term CO trends in the atmosphere”?
- Again, please provide the reference for the Mauna Loa CO measurements? There are measurements after 2003.
- Figure 7.
- Are you plotting monthly means?
- How do you define your UT and LT here for the simulated CO?
- What do the letters and numbers mean in subplot b. Are they needed if you defined the colors to be different seasons.
- Mauna Loa and IAGOS CO measurements are for a specific altitude while MOPITT CO retrievals are for partial columns. They are not representative of the same exact location. Please reference previous papers on MOPITT CO data that have looked at trends.
- Figure 10:
- What is x in your equations for temporal trend analyses? And what is the unit of the slope in those equations?
- It is hard to see the MOPITT data points and the trend lines.
Citation: https://doi.org/10.5194/egusphere-2024-2414-RC2 -
AC2: 'Reply on RC2', Kuo-Ying Wang, 28 Feb 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC2-supplement.pdf
-
AC5: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC5-supplement.pdf
-
RC3: 'Comment on egusphere-2024-2414', Anonymous Referee #3, 07 Oct 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-RC3-supplement.pdf
-
AC3: 'Reply on RC3', Kuo-Ying Wang, 28 Feb 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC3-supplement.pdf
-
AC6: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC6-supplement.pdf
-
AC3: 'Reply on RC3', Kuo-Ying Wang, 28 Feb 2025
-
AC4: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC4-supplement.pdf
-
AC5: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC5-supplement.pdf
-
AC6: 'Comment on egusphere-2024-2414', Kuo-Ying Wang, 07 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-2414/egusphere-2024-2414-AC6-supplement.pdf
Viewed
Total article views: 797 (including HTML, PDF, and XML)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 312 | 110 | 375 | 797 | 23 | 14 |
- HTML: 312
- PDF: 110
- XML: 375
- Total: 797
- BibTeX: 23
- EndNote: 14
Cumulative views and downloads
(calculated since 20 Aug 2024)
Viewed (geographical distribution)
Total article views: 820 (including HTML, PDF, and XML)
Thereof 820 with geography defined
and 0 with unknown origin.
| Country | # | Views | % |
|---|---|---|---|
| United States of America | 1 | 241 | 29 |
| Germany | 2 | 58 | 7 |
| Romania | 3 | 49 | 5 |
| China | 4 | 30 | 3 |
| Israel | 5 | 27 | 3 |
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
- 241
1
241
Latest update: 04 Apr 2025
Kuo-Ying Wang
CORRESPONDING AUTHOR
Department of Atmospheric Sciences, National Central University, Chung-Li, Taiwan
Philippe Nedelec
Laboratoire d’Aérologie, Centre National de la Recherche Scientifique, Observatoire Midi-Pyrénées, 14 Avenue E. Belin, 31400 Toulouse, France
Valerie Thouret
Laboratoire d’Aérologie, Centre National de la Recherche Scientifique, Observatoire Midi-Pyrénées, 14 Avenue E. Belin, 31400 Toulouse, France
Hannah Clark
Laboratoire d’Aérologie, Centre National de la Recherche Scientifique, Observatoire Midi-Pyrénées, 14 Avenue E. Belin, 31400 Toulouse, France
Andreas Wahner
Forschungszentrum Julich GmbH, Institut fur Energie und Klimaforschung, IEK-8 Troposphare, 52425 Julich, Germany
Andreas Petzold
Forschungszentrum Julich GmbH, Institut fur Energie und Klimaforschung, IEK-8 Troposphare, 52425 Julich, Germany
Short summary
We use routine in-service commercial passenger airplanes Airbus A340 and A330 to collect air pollutants in the upper troposphere. The beauty in using commercial airplanes is that these commercial airplanes, like taxi on the ground, keep flying all the time. We find that short-lived air pollutants are very sensitive to ground-level emissions. Effective regulation in ground-level emissions can help to reduce air pollution in the upper troposphere.
We use routine in-service commercial passenger airplanes Airbus A340 and A330 to collect air...